Unraveling ice multiplication in winter orographic clouds via in-situ observations, remote sensing and modeling

Recent years have shown that secondary ice production (SIP) is ubiquitous, affecting all clouds from polar to tropical regions. SIP is not described well in models and may explain biases in warm mixed-phase cloud ice content and structure. Through modeling constrained by in-situ observations and its synergy with radar we show that SIP in orographic clouds exert a profound impact on the vertical distribution of hydrometeors and precipitation, especially in seeder-feeder cloud configurations. The mesoscale model simulations coupled with a radar simulator strongly support that enhanced aggregation and SIP through ice-ice collisions contribute to observed spectral bimodalities, skewing the Doppler spectra toward the slower-falling side at temperatures within the dendritic growth layer, ranging from −20 °C to −10 °C. This unique signature provides an opportunity to infer long-term SIP occurrences from the global cloud radar data archive, particularly for this underexplored temperature regime.

The default temperature-dependent scheme of the Weather Research and Forecasting (WRF) model shows a gradual increase in simulated ice crystal number concentrations (ICNCs), reaching peak concentrations exceeding 100 L -1 at temperatures below -30°C (Fig. 2a).However, when replacing the default primary ice production parameterizations with the aerosol-aware scheme utilized in the DEMOTT simulation, the coldertemperature ICNCs are reduced, with predicted values consistently remaining below 50 L -1 (Fig. 2b).It is worth noting here that the aerosol information used to constrain the Demott 1 parameterization was derived from the altitude of Helmos Hellenic Atmospheric Aerosol and Climate Change (HAC) 2 , which is ∼500 m higher than the "Vathia Lakka" (VL) station.Although this may lead to slight underestimations of the ice nucleating particles (INPs) at lower altitudes and, conversely, an INP overestimation at altitudes above (HAC) 2 , DEMOTT still predicts much lower ICNCs than CONTROL at cold temperatures and provides a more realistic representation of the upper-level INPs.Reducing the predicted ICNCs increases the liquid water content (LWC) present at temperatures below -20°C (Fig. 3b), which is non-existent for CONTROL (Fig. 3a).During the 3 rd cloud period, in the absence of seeding ice particles from above, higher ICNCs predicted by CONTROL lead to effective growth through riming and WBF, allowing for differential settling and justifying the enhanced aggregation rates compared to DEMOTT (Figs. 2a, b).

Supplementary Text 2: Modeling uncertainties during the low-level orographic cloud period
In the orographic cloud persisting after the passage of the seeder cloud (3 rd turquoise box in Fig. 1a), notable spikes of enhanced radar equivalent reflectivity factor (Zew) are observed, which are not fully captured by the simulation that accounts for ice multiplication, referred to as ALLSIP (Fig. 1d), but are comparatively better reproduced by the CONTROL and DEMOTT simulations (Figs.1b, c).This is further supported by median profiles extracted from this period, wherein the predictions of the two simulations incorporating solely PIP parameterizations align more closely with the observations (Supplementary Fig. 4).The inefficiency of the ALLSIP simulation in replicating the observed Zew spikes might stem from uncertainties in the representation of implemented secondary ice production mechanisms within the bulk microphysics framework.For instance, Sotiropoulou 2 found that adopting an emulated bin framework for collisional break-up and droplet-shattering could enhance simulated ice multiplication rates, albeit with increased computational demand.Given the prevailing stormy conditions during the case study (Supplementary Fig. 2c), various surface-based processes such as blowing snow or detachment of surface hoar frost 3 could have potentially contributed to the observed instances of enhanced Zew close to the surface.Simplified methods to simulate such processes have been explored for orographic MPCs 4,5 , yet it would be intriguing to explore more sophisticated and advanced modeling frameworks 6,7 .Other than ice multiplication and surface-based processes, microphysical processes such as preactivation of INPs 8,9 , as demonstrated for example in Yang 10 for tropical maritime stratiform clouds, may also be important ICNC sources.
An additional plausible explanation might involve the underrepresentation of specific INP types.As shown by Gao 11 , biological INPs play a crucial role, especially when the (HAC) 2 station is affected by the planetary boundary layer (PBL) or is located close to cloud topconditions that are frequently met during the 3 rd cloud period (see black circles in Supplementary Fig. 5).Biological INPs, active at relatively warm temperatures higher than -15°C, are indeed not considered in the DeMott 1 scheme.

Supplementary Text 3: Physics options employed in WRF
WRF is forced with initial and 6-hourly boundary conditions from the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalyses dataset (ERA5) 12 .The use of high-resolution ERA5 data (0.36°) for initializing WRF has been found to outperform the near real-time Global Forecasting System (GFS) data from the National Centers for Environmental Protection (NCEP), which has a spatial resolution of 1° (not shown).The static fields at each model grid point, including topography and land use fields, were sourced from default WRF preprocessing system datasets with a resolution of 30''.The land use categories were based on the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover classification.In terms of physics options, we employed the Rapid Radiative Transfer Model for General Circulation Models (RRTMG) radiation scheme to parameterize both shortwave and long-wave radiative transfer.The PBL physics were represented using the non-local, first-order closure YSU (Yonsei University) scheme 13 , coupled with its associated surface layer scheme.A sensitivity simulation revealed that YSU outperformed the local Mellor-Yamada-Janjić (MYJ) 14 1.5 order scheme (not shown) in terms of meteorological observations.Surface processes were modeled using the Noah land surface model (Noah LSM) 15 .The Kain-Fritsch cumulus parameterization was only activated in the 12-km resolution domain, as the resolution of the two nested domains was deemed sufficient to reasonably resolve cumulus cloud processes at the grid scale.

Supplementary Text 4: INP measurements at (HAC) 2
The Portable Ice Nucleation Experiment (PINE) is an innovative instrument designed for ice nucleation studies and long-term field observations of ice nucleating particles (INPs) across a wide temperature range.During the Cloud-AerosoL InteractionS in the Helmos background TropOsphere (CALISHTO) campaign, PINE was operated at the mountain-top site of (HAC) 2 .PINE employs a pumped expansion principle to generate ice and water supersaturated conditions for testing the ice nucleation ability of aerosol particles.The instrument operates in repetitive cycles, involving the sampling of aerosol into a precooled cloud chamber, activation of aerosol particles as supercooled droplets and ice crystals through the expansion of air inside the chamber, and subsequent refilling of the cloud chamber with fresh aerosol for the next cycle.A more detailed description of the PINE instrument can be found in Möhler 16 .The INP measurements presented in Complementary Fig. 10a correspond to the period spanning one month, from the end of October to the end of November 2021.A comprehensive analysis of INP sources during CALISHTO is provided in Gao 11 .